Journal of Quality Engineering and Management

Abstract  Control charts are the most popular statistical process control tools for quickly discovering process changes. Among the univariate control charts, the 𝑋 ̅ control chart is more popular. In the economic and the economic-statistical design of control charts, constant and known values are often assumed for input parameters (cost and process parameters). In the real world, these parameters are not fully known and are unknown. The purpose of this paper is to present a simple model for the design of economic and economic-statistical robustness control charts using the Lorenzen and Vance cost model under multiple scenarios and then compare it with other robust economic and economic-statistical designs. The optimal values of the parameters are obtained by genetic algorithm. Comparison economic, robust economic, and robust economic-statistical designs shows that a weighted economic-statistical robustness design performs better than other robust designs. The proposed design is economically weaker, but its statistical performance is better than other robust designs. In addition, it is much easier to use in practice than other methods. 
 
 

Abstract  Today, with the planning of a sustainable supply chain, in addition to achieving economic goals, it can satisfy the social and environmental objectives and considerations, which result in a competitive advantage and increase chain power. However, the effects of implementing the principles of sustainability on the resilience of a supply chain in various disruptions have not yet been deeply studied by the researchers. The resilience supply chain, with the benefit of a resilient supply portfolio, can reduce the risk and vulnerability of supply chains to the extent possible in the face of disturbances such as supply disruptions. In this research, modeling and problem solving of a sustainable resilience planning problem of a four-level supply chain network are discussed. For this purpose, a multi-objective optimization model is developed for this problem. The objectives of the proposed model include minimizing cost, maximization of social and environmental outcomes of the suppliers, as well as minimizing delays in the delivery of products. Two methods of Augmented Epsilon constraint and Lp metric are used for balancing goals. Finally, in the final section of the study, a numerical study is considered. Finally, in the final section of the study, the numerical study is considered. The outputs of the model and the sensitivity analysis indicated that the model was efficient. 
 
 
 

Abstract In this study, a new bi-objective model along with a novel solving method are provided to address the non-exponential RAP in series-parallel systems with repairable components. The proposed method is based on optimization via simulation approach and artificial neural network technique. In addition, to be more realistic, discounts strategies for purchasing the components are employed during modeling. The main objective of the model is to maximize mean time to the first failure (MTTFF) of the system via allocating the best redundant components for each subsystem. Since, the components’ failure rate has non-exponential distribution, the simulation technique and ANN are applied to find the MTTFF. To solve the problem, some meta-heuristic algorithms integrated with the simulation method. Several numerical examples are carried out to test the proposed approach and as the results show, the proposed approach is much more real than previous ones and also the near optimum solutions are achieved. 
 

Abstract  
The length of waiting time is considered as a key determinant of patient satisfaction level; besides, it has a significant impact on the effectiveness and quality of services which are provided to patients. In addition, Simulation study is also considered as an effective tool for improving patient flow, reducing waiting time and increasing patient satisfaction. Hence, in the present study we made use of simulation to improve the quality of health care in a urology unit which is a part of a kidney center in Tehran. Put differently, the aim of the current study was increasing the efficiency of Extracorporeal Shock Wave Lithotripsy (ESWL) method besides reducing the waiting times and the patient cancellation rates. Therefore, a Discrete-Event Simulation model was developed using iGrafx software, which was later used in conjunction with MATLAB software to form and evaluate the urology unit improvement scenarios in three categories: changing technicians’ presence schedules during different shifts, changing the schedule of patient visits, and examining the factors that reduce the patient cancellation rate. The greatest differences were resulted from the employment of scheduling scenarios of patient visits on waiting time and duration of stay with averages of 23.33 and 22.81 minutes, respectively. In addition, the results of examining the factors that reduce patient cancellation rate demonstrated that the number of cancellations were decreased with an average of 1.44 cases per day. In each category of proposed scenarios, applying changes based on the selected scenario of that category led to significant improvements in performance criteria of the urology unit. It is also worth mentioning that the impact of scheduling scenarios of patient visits was much higher than other scenarios. 

Abstract  Wind Turbines (WT) are one of the fastest growing sources of power production in the world today and there is a constant need to reduce the costs of operating and maintaining them. Condition monitoring (CM) is a tool commonly employed for the early detection of faults/failures so as to minimise downtime and maximize productivity. In this paper, we examine the statuses of wind turbine condition monitoring, maintenance strategy, signal processing methods, SCADA system and criterion design of condition monitoring system failure. The purpose of this paper is to develop a method of interpreting information collected from wind turbines via SCADA using state-of-the-art science that was not used in the past due to the lack of appropriate analytical tools. Indeed, by integrating condition monitoring, SCADA data analysis and signal processing, a new approach is introduced that reduces maintenance costs by monitoring all mechanical and electrical components. 
 

Abstract Privatization is considered as an approach to help organizations and corporates to achieve high efficiency in developing countries. Therefore, the way it affects the corporate performance is of great importance, because privatization and organizational excellence are so complicated due to feedback relationships, time delays, and dominant non-linear relationships. Moreover, the dynamics of the privatization’s effects on organizational excellence over time should be analyzed using a system dynamics approach in order to examine the effectiveness of privatization so that it can help corporates to make appropriate decisions and invest on the privatizations aspects with highest impact on organizational excellence. Privatization has not analyzed using the system dynamics approach in previous studies. Thus, this study aims to analyze and model the privatization’s effect on corporate performance using the system dynamics approach and EFQM excellence model in five stages in the National Iranian Drilling Company. After the statement of the problem, the key variables are identified and the time horizon is determined. Then, the dynamic hypothesis is presented and the structure of a causal loop diagram is depicted. The surface and flow maps are also explained and the model is simulated. Afterwards, the validity of the proposed model is examined based on validation tests. Finally, by analyzing the sensitivity of the model variables, designing and evaluating policies at the National Iranian Drilling Company are dealt with. Analyzing the impact of privatization on organizational excellence creates a set of advantages for the company using the dynamism systems, the most important ones are: simulating the effects of affective factors on the results; implementing "what if" to analyze the scenarios and potential. future threats; The ability to visually performance the relationship between privatization and organizational excellence; reduce the risk of executive programs by simulating and examining the consequences of different scenarios before implementing the dynamic model; and considering the time reliance between cause and effect. The effects of any changes can be simulated before practical application by using the proposed model in a virtual environment, and decision can be made by complete knowledge of all aspects.